[CLOSED] Management of Machine Learning Model Lifecycle

You will assist with 1. Conducting data cleaning and predictive machine learning modelling, including retraining and refining existing predictive models used in MND. 2. the deployment of these models directly within our analytical environment (AWS SageMaker AI) for usage in downstream data products. 3. Monitoring and improving model performance via hyperparameter tuning or similar methods. 4. Exploring feasibility and expirement with latest AI tools to enable a bot to allow users to 'chat with their municipal data'. 1. Reviewing and expanding the existing suite of predictive models, such as, the Satisfaction Hotspot Model and Feedback Volume Forecasting Model. This project will provide an intern with hands on experience in the entire life cycle of a model including data preparation, choosing the right models, training, testing and creating an automated workflow for regular retraining & udates. 2. Exploring how commercial LLM tools can enhance the value-add of the Analytics team, such as being able to call on e.g. GPT-o5 to assist with large scale sentiment analysis / tasks which require high compute power. The ideal candidate is someone who is proficient in Python programming for data pre-processing, data modelling and is familiar with technical data infrastructure setup for model training, retraining and deployment.